Jira service management - request management

The Jira Service Management report is a tool that provides detailed information about the activities and performance of the technical support team. The content of the report depends on the configuration and metrics the company has chosen to track.

Information that can be found in the report is divided into:
1. Basic issues metrics used to analyze the workload of the support team and the dynamics of issues:

• number of open, closed and in progress issues
• increase in issues number over time on a daily basis and by day of the week in time intervals – used to assess how many issues are coming in, which may indicate increases or decreases in the demand for support and may point out the occurrence of failures

2. SLA (Service Level Agreement) and SLI (Service Level Indicators) – used to analyze the performance of the support team and the implementation of agreed response / resolution time, and subsequently also to decide whether the processes require optimization. Shows whether the team is meeting customer expectations and contractual obligations.

• response time
• resolution time

3. Issues categorization – types and priorities – analysis of the dominant types of problems, assessment of the quality of the supported processes and systems (number of critical issues and failures).

4. Team analysis – team member efficiency and even distribution of work

• efficiency of individual team members (number of issues handled and average processing time)
• team load – number of issues per employee

5. Trends and charts

• data comparison over time – number of issues over periods, trends in processing time

6. Control of response to issues – list of issues requiring urgent attention due to priority and/or exceeding SLA.

The Jira Service Management report is a valuable tool for support team managers, allowing them to monitor efficiency, identify problems, and make decisions about resource allocation. By analyzing data from the report, you can increase customer satisfaction, improve processes, and predict future support needs.